PROJECT SUMMARY/ABSTRACT High blood pressure (BP) is a major cardiovascular risk factor that is treatable, yet hypertension awareness and control rates are low. Ubiquitous BP monitoring technology could improve hypertension management, but existing devices require an inflatable cuff and thus do not afford anytime, anywhere measurement of BP. The broad goal of this project is to extend the oscillometric principle, which is applied by most automatic cuff devices, for cuff-less and calibration-free monitoring of BP via only a smartphone. The idea is for the user to serve as the actuator (instead of the cuff) by pressing her fingertip against the phone to steadily increase the external pressure of the underlying artery, while the phone serves as the sensor (rather than the cuff) by measuring the applied pressure and resulting variable-amplitude blood volume oscillations. The phone also provides visual feedback to guide the finger actuation and applies an algorithm to compute BP from the measurements just like a cuff. A smartphone-based device for BP monitoring via this oscillometric finger pressing method will be established. The specific aims are: (1) to develop an advanced sensor-unit to robustly measure the finger blood volume and applied finger pressure; (2) to develop an advanced algorithm to accurately compute BP from the measurements in a diverse user population; and (3) to validate the integrated device according to a widely accepted protocol. An initial device will be developed to acquire a comprehensive set of potentially useful measurements including the pulsatile component of the finger pressure arising from the tonometric principle. This device will consist of a multi- photoplethysmography sensor array to identify the location of the finger artery and measure the blood volume oscillations from therein and a multi-force sensor array to measure the area of force application. The advanced sensor-unit will mitigate the impact of imprecise finger positioning. A training dataset will be collected with this device and cuff-based devices in a diverse user population. This dataset will be analyzed to develop an algorithm to accurately compute BP. The algorithm will include leveraging the smartphone camera and image processing to obtain the BP measurement at heart level and computing finger and brachial systolic, diastolic, and mean BP based on various physiologic models of the measurements. A final smartphone-based device will be built that incorporates the requisite sensing and algorithm. The device will be prospectively tested according to the standard Association for the Advancement of Medical Instrumentation protocol for automatic cuff devices. This protocol includes 85 subjects encompassing a wide BP range with auscultation cuff BP as the reference. Successful completion of this project could ultimately translate to widespread BP monitoring and thereby help reduce the incidence of cardiovascular mortality.